Microwave vegetation indexes derived from satellite microwave radiometers

Major uncertainties in deriving vegetation indices from satellite measurements are the effects of atmosphere and background soil conditions. Through numerical simulations by surface emission model - Advanced Integral Equation Model (AIEM), we found that bare surface emissivities at different frequencies can be well characterized by a linear function with parameters that are dependent on the pair of frequencies to be used. This makes it possible to minimize the surface emission signal and maximize the vegetation signal when using multi- frequency radiometer measurements. Using the radiative transfer model (omega-tau model), a linear relationship between the brightness temperatures observed at two adjacent radiometer frequencies can be derived. It can be shown that the microwave vegetation index derived by the intercept and slope of this linear function depends only on vegetation properties and can be derived from the dual-frequency and dual-polarization measurements. We will demonstrate the theoretical basis of this new microwave vegetation index and show comparisons of the microwave derived vegetation index with the optical sensor derived NDVI measurements.